This year’s theme:
Socially-aware Crowdsourcing – The Value of the Human Touch
Aims and Scope
Both crowdsourcing and human computation consider humans as distributed task-solvers, with the latter embedding human users as a part of intelligent computational systems. They both leverage human reasoning to solve complex tasks that are easy for individuals but difficult for purely computational approaches (human computation) or for traditional organisational work arrangements (crowdsourcing). Effective realisations of these paradigms typically require participation of a large number of distributed users over the Internet, a careful design of task structures, participation incentives and mechanisms for coordinating and aggregating results of individual participants into collective solutions.
Though rarely explicitly addressed as such, social media and related technologies often provide the enabling methods and technologies for the realisation of such models. Examples include crowdsourcing marketplaces (e.g. Amazon Mechanical Turk), crowdsourcing service providers (e.g. Microtask, CrowdFlower) or games with a purpose. While centralised platforms are also at the core of “traditional” approaches to collective intelligence (e.g. Wikipedia), attention is increasingly turning to the possibilities of harnessing existing social platforms (e.g. Facebook, Twitter) that already gather huge numbers of users into webs of social relationships.
For instance, such relationships allow the development of new kinds of task routing mechanisms (e.g. identifying the best or most trusted participants for a specific task), while social incentives can reflect community-like phenomena (e.g. the reputation economy). This is already leading to experiments such as expert-based crowdsourcing or solutions for task-injection across distributed social platforms. It is also partially reflected in growing research on inferring social influence, attention or trust from online social exchanges with the aim of providing mechanisms for more effective information exchanges or collective problem solving. Socially-aware human computation and crowdsourcing systems call for new work division and execution mechanisms, where the traditional individual “tayloristic” model evolves into a collaborativa labour environment featuring direct communication and collaboration between the users, and private exchanges between the task-owner and the task-solver.
This begs the question of how such more open, participatory models of collective action can inform the development of new kinds of crowdsourcing and human computation systems and approaches:
- Can we conceptualize specific classes of human computation as instances of different forms of social collaboration?
- How can we design crowdsourcing and human computation systems where the involvement of a large number of diverse human users as providers, aggregators or “processors” of information leads to outcomes that benefit the entire collective rather than only individual contributors, task owners or commissioners of work assignments?
- How can the theory of collective action inform the design of such collaborative approaches to socially-aware crowdsourcing and human computation?
- What are the different sources of value of the “human touch” that can be brought to bear through such new approaches?
The SoHuman 2014 workshop aims at bringing together researchers and practitioners from different disciplines to explore the challenges and opportunities of novel approaches to collective intelligence, crowdsourcing and human computation that address social aspects as a core element of their design principles, implementations or scientific investigation.
We are especially interested in applications and investigations in a range of domains such as collective action and social deliberation, multimedia search and exploration, enterprise and medical applications, cultural heritage, social data analysis or citizen science.
Topics of Interest
Topics to be discussed in this special issue include (but are not limited to) the following:
- Social media in collective intelligence systems
- Use cases and applications of social media to crowdsourcing and human computation
- Social incentive models for crowdsourcing and human computation
- Social-network analysis for crowdsourcing and human computation
- Applications of social media visualisation to collective intelligence applications
- Social coordination in crowdsourcing and human computation
- Social search and human computation
- Trust models for collective intelligence and crowdsourcing
- Semantic modelling in crowdsourcing and human computation
- Expert-based crowdsourcing
- Influence metering and social trust models
- Expertise-inference techniques and their application to task routing
- Reputation systems for human computation
- Quality assurance in distributed human intelligence tasks
- Social sensing in crowdsourcing and human computation
- Domain-specific challenges in crowdsourcing and human computation
Jasminko Novak, European Institute for Participatory Media / Univ. of Appl. Sciences Stralsund
Alessandro Bozzon, Delft University of Technology
Piero Fraternali, Politecnico di Milano
Petros Daras, ITI CERTH
Otto Chrons, Microtask
Bonnie Nardi, UC Irvine
Alejandro Jaimes, Yahoo Research
We welcome submissions describing ideas, experiments, and application visions originating from requirements for, and efforts aimed at, supporting crowdsourced and human computation tasks. We encourage the following submission types:
- Regular research papers (6-8 pages)
- Applications / Demonstrators (4 pages)
- Position papers (2-4 pages)
Submissions should describe the innovative aspects of the work they present, highlighting pros and cons with respect to related work. Demo proposals should describe clearly what will be demonstrated and how the contributions will be illustrated interactively. Optionally, proposals can include a URL that shows a preliminary version of the demo (e.g., screenshots, videos, or a running system).
All submissions will be reviewed in a peer-review process by at least two members of the program committee. All submission must be formatted according to Springer LNCS paper formatting guidelines (http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0). All submissions will be done electronically via the SoHuman 2014 web submission system.
At least one author of each paper will need to register for the conference and attend the workshop to present the paper. Accepted workshop papers will appear in Springer’s Lecture Note Series in Computer Science as part of the conference proceedings but we also allow accepted papers to be presented without publication in the proceedings, if the authors prefer to do so. In addition, selected workshop papers will be invited for submission of an extended version to a fast-track special issue of the interdisciplinary journal Human Computation.
Klemens Böhm, Karlsruhe Institute of Technology
Marco Brambilla, Politecnico di Milano
Simon Caton, Karlsruhe Institute of Technology
Fausto Giunchiglia, University of Trento
Martha Larson, Delft University of Technology
Pietro Michelucci, Strategic Analysis, Inc.
Naeem Ramzan, University of West of Scotland
Marcello Sarini, University of Milano-Bicocca
Mohammad Soleymani, University of Geneva, Switzerland
Maja Vukovic, IBM T.J. Watson Research
Lora Aroyo, VU University Amsterdam
Gianluca Demartini, University of Fribourg
Apostolos Axenopoulos, CERTH (tbc)
Gabriella Kazai, Microsoft Research (tbc)
Ville Miettinen, Microtask (tbc)
Aaron Shaw, Harvard University (tbc)
Wolfgang Prinz, Fraunhofer FIT/RWTH Aachen (tbc)